# | Date | Teacher | Title |
---|---|---|---|
1 | 10/02/2022 | U. Simsekli | Introduction |
2 | 17/02/2022 | Alessandro Rudi Ulysse Marteau-Ferey |
Supervised
learning and linear regression TD1 (Data: classificationA_train, classificationA_test, classificationB_train, classificationB_test, classificationC_train, classificationC_test, mnist_digits.mat, solution, NEW: all in one zip: ALL) |
3 | 24/02/2022 | Alessandro Rudi Ulysse Marteau-Ferey |
Logistic
regression and convex analysis TD3, |
03/03/2022 | |
No Class | |
4 | 10/03/2022 | Alessandro Rudi Ulysse Marteau-Ferey |
Convex
optimization
TD4, TD4-english-version, solution to theoretical questions, solution to practical questions |
5 | 17/03/2022 | Alessandro Rudi Ulysse Marteau-Ferey |
Kernels
Exercise sheet, solution |
6 | 24/03/2022 | Alessandro Rudi Ulysse Marteau-Ferey |
Learning with Kernels Numerical tour of Ridge and Lasso by Gabriel Peyre |
7 | 31/03/2022 | Alessandro Rudi Ulysse Marteau-Ferey |
Elements of Statistical Machine Learning Numerical tour of logistic classification by Gabriel Peyre , solution and slight nodification , data for first part |
8 | 07/04/2022 | Umut Simsekli Ulysse Marteau-Ferey |
Model Based ML - Maximum Likelihood TD on sgd , data , solution to the TD on SGD , |
9 | 14/04/2022 | Umut Simsekli Ulysse Marteau-Ferey |
Unsupervised Learning TD on KNN , Small recap on KNN , data , TD on PCA , solution to the TD on KNN |
10 | 21/04/2022 | Umut Simsekli Ulysse Marteau-Ferey |
MCMC Sampling, lecture notes
TD on MCMC , Solution to the TD on MCMC |
28/04/2022 | |
No Class |
|
05/05/2022 | |
No Class |
|
11 | 12/05/2022 | Umut Simsekli Ulysse Marteau-Ferey |
Neural Networks TD on Neural Networks |
12 | 19/05/2022 | Umut Simsekli Ulysse Marteau-Ferey |
Summary |
26/05/2022 | |
No Class |
|
13 | 02/06/2022 | Alessandro Rudi Umut Simsekli |
Exam
8h30 to 12h30, the room H. Cartan. You can bring your notes. |